In brief: Technologies and scientific methods for real-time seismology are advancing rapidly at present. In some areas, steady evolution of already maturing technologies can deliver important improvements for dynamic risk assessment. In selected areas, new and emerging technologies in sensors, communication or big data analysis may have the potential for a transformative change. RISE prioritises these tasks to exploit these opportunities:
- Innovative sensors and sensor networks: We will explore the utility and value of innovative sensor technologies that offer the potential to increase the spatial sampling by orders of magnitude. We will exploit Distributed Acoustic Sensing (DAS) using dedicated or existing fibre-optics cables, as well as next generation lower-cost wireless or wired sensors and hyper-dense networks.
- Promote advances in observational capabilities: Innovative processing, machine learning and deep learning approaches have the potential to revolutionise the way seismic networks operate; they also demand new approaches to data access and archiving. Likewise, big-data approaches can be used to develop dynamic and high-resolution models for exposure and associated loss.
- Seek earthquake precursors in big-data applications, such as using ambient noise correlations to systematically monitor thousands of stations for changes in seismic wave velocity and attenuation.
- Portable excitation sources for field-testing of existing and densely instrumented structures.
Lead: University of Edinburgh UEDIN
Participants: ETH Zürich, GFZ, INGV, IMO, UNIBO, UNINA, EUCENTRE, UGA, BOUN, KNMI, ST-I, UKRI, QUAKE
Contact: Prof. Ian Main